What Do Asteroids Have To Do With Location Targeting?

It’s an accepted principle of physics that the same object cannot be in two places at the same time. As a result, location and time are actually the most important factors in determining the similarity or difference between entities.

Based on this principle, Jeff Jones, chief scientist, complex computing at IBM, aided in the creation of a model that can more efficiently predict the trajectory of asteroids over 25 years based on which of the celestial bodies have shared a certain “box” of space on same day.

In the most simplistic terms, knowing exactly where the asteroids have been and when — both individually and in relation to each other — has near limitless potential when combined with the power of computing.

“The most competitive organizations are going to make sense of [the data] they are observing fast enough to do something about it while its still happening, and geo-spatial technology is the fuel that powers this,” Jones said in a session at GeoBuiz Summit April 26. This line of thinking can effectually be applied to everything from astrophysics to maritime navigation — to, yes, location targeting.

Movement Enables ‘Powerful Predictions’

When it comes to fusing consumer data from multiple sources, it’s important to find out how people are alike while still understanding them as unique individuals — that’s “entity resolution,” Jones said.

So how does this space-time location tie in? Well, one key distinguishing feature between, say, family members who could share many things — a home, a name, a computer, perhaps a birthdate, etc. — is the pattern of their movements and their relative locations at various times. This can be determined based on data from their mobile and connected devices.

“Space and time are analytic superfood,” Jones said. In other words, contextual location can say considerably more about individuals than many other data points combined. As Sonata’s Lara Mehanna put it in an earlier interview, “where you are is who you are.”

Jones touched on a variety of complex computing use cases for space-time interaction, but it’s easy to see how this kind of understanding relates to building consumer profiles. By distinguishing individuals, understanding the locations they frequent, and using predictive modeling to know where they are likely to go next, marketers can improve ad targeting as well as the overall consumer experience.

“600 billion transactions are created by smartphones in the US alone per day — that’s a lot of geo-data,” Jones concluded. “Your movement quickly identifies where you spend your time — and [that allows for] powerful predictions.”

So, sure, marketers don’t have to worry about asteroids colliding. But understanding consumers’ contextual location — and building profiles accordingly — is still what puts them on the right path.